Research on Credit Risk Evaluation of SMEs in Supply Chain Finance based on Big Data

DOI

10.2991/wrarm-19.2019.27How to use a DOI?

Keywords

supply chain finance, credit risk, logistic model

Abstract

With the development of global supply chain, enterprises are more and more aware of the advantages of supply chain. In recent years, supply chain finance has become the focus of many logistics enterprises and financial institutions. In this paper, principal component analysis and logistic regression method are used to further analyze the credit risk of SMEs under the supply chain financial model, so as to provide a theoretical basis for improving the credit risk assessment method and making correct decisions.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaofei Luan
AU  - Hongmei Zhang
PY  - 2019/09
DA  - 2019/09
TI  - Research on Credit Risk Evaluation of SMEs in Supply Chain Finance based on Big Data
BT  - Proceedings of the Sixth Symposium of Risk Analysis and Risk Management in Western China (WRARM 2019)
PB  - Atlantis Press
SP  - 132
EP  - 136
SN  - 1951-6851
UR  - https://doi.org/10.2991/wrarm-19.2019.27
DO  - 10.2991/wrarm-19.2019.27
ID  - Luan2019/09
ER  -